Google Cloud Partner AI Series | Iliana Quinonez, Google Cloud, & Rajeev Nayar, Tiger Analytics

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Rajeev Nayar

Vice President, Data & AI

Tiger Analytics

Iliana Quinonez

Director, North America Startups, Customer Engineering

Google Cloud

play_circle_outline Overview of Tiger Analytics as a significant data and AI provider since 2011.

play_circle_outline Collaboration between Google Cloud and Tiger Analytics to solve business challenges effectively.

play_circle_outline Joint e-commerce platform project using Google Cloud and Vertex AI to enhance digital search.

play_circle_outline Enhancing Service Efficiency: How Tiger Analytics Utilizes Agentic Frameworks and Partnership Feedback to Slash Costs and Optimize Outcomes

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Iliana Quinonez, Google Cloud, & Rajeev Nayar, Tiger Analytics

Rajeev Nayar

Vice President, Data & AI Tiger Analytics

Iliana Quinonez

Director, North America Startups, Customer Engineering Google Cloud

In this Google Cloud Partner AI Series interview, theCUBE’s Rebecca Knight sits down with Iliana Quinonez, director, North America startups, customer engineering at Google Cloud, and Rajeev Nayar, VP of data and AI at Tiger Analytics, to unpack how the partnership is turning AI ambition into measurable outcomes. Quinonez explains how Google Cloud provides the secure data foundation and vertical AI stack, while Tiger translates technology into tangible business value with industry solutions. Nayar details real-world wins, from multilingual e-commerce search la... Read more

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What is the history and partnership background of Tiger in relation to data and AI? add

How does the partnership leverage cloud infrastructure and expertise to provide insights and solutions for customers? add

What was the purpose of the joint press release involving Google and Tiger? add

What are the tangible business outcomes and benefits associated with the partnership between the technology company and Tiger, including cost reductions and customer feedback? add

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Iliana Quinonez, Google Cloud, & Rajeev Nayar, Tiger Analytics

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Rebecca Knight

>> Hello and welcome to theCUBE Studios in Palo Alto and the Google Cloud Partner AI series. I'm your host, Rebecca Knight. We've got two fantastic guests for this next segment. I would like to welcome Rajeev Nayar, vice president data and AI at Tiger Analytics. Welcome, Rajeev.

Rajeev Nayar

>> Thank you.

Rebecca Knight

>> And Iliana Quinonez, director North America startups, customer engineering at Google Cloud. Welcome.

Iliana Quinonez

>> Thank you, Rebecca.

Rebecca Knight

>> Rajeev, I want to start with you. For our viewers who might be unfamiliar with Tiger Analytics. Can you talk about what you do and how you fit in the Google Cloud ecosystem?

Rajeev Nayar

>> So, Tiger has been around since 2011 and we are one of the largest or fastest-growing pure-play data and AI providers. And we've been growing significantly in the space, helping our customers get value out of AI. And Google has been a very close partner. We've been working together on multiple accounts where together we have taken some of these newer things that Google is doing and delivered value to our customers.

Rebecca Knight

>> Excellent. Now, Iliana, from your perspective, what makes Tiger such a strong partner in the AI and data space?

Iliana Quinonez

>> Thank you for the question. And I have to say Rajeev and his company have done amazing job with our customers. So, I have to call out a couple of things. When we have a partnership, we really look for that value that their partners can bring to our customers and really translating what they can do with technology into something that's tangible for their business with real outcomes, with real benefits and solving a real problem they may have. So, that's one area. And the other area is just to know that they love technology and are as passionate about technology and AI as we are. So, that actually really help us out to have the synergies really well.

Rebecca Knight

>> Rajeev, there are so many challenges that business leaders are grappling with as they try to embrace this era of agentic AI. What are some of the top challenges you are hearing in your conversations with business leaders, especially as they're trying to derive meaningful insights to drive business value?

Rajeev Nayar

>> A few, actually. One of the big ones that we hear about now is the ROI from their AI investments. There's a lot of discussion around that. One of the things that people are beginning to realize is good AI requires good data. So, building the foundation of the data, making sure that you invest in that so that you can actually both scale your AI and get value out of it is becoming a critical issue. The third thing is there are a lot of experiments happening, but being able to take that and then put it into production so that you actually make decisions with this and then generate business value, that's another thing that people are grappling with.

Rebecca Knight

>> So, Iliana, we've heard about the challenges and the problems. How are Google Cloud and Tiger Analytics working together and how do they complement each other to solve some of these problems and deliver better outcomes?

Iliana Quinonez

>> Yeah. Well, as you know, so cloud is something that we provide and we've been in this market for a long time, so our strength is actually host the data, secure the data, and really make sure that it's available and ready for when the customers want to use it. But here's the thing, so with tiger, what we have is the ability to actually provide insights, provide the return, metrics, the results from that data that we are being the custodians for. So, that's one area that we complement each other really well. So, we provide infrastructure, a vertical stack for AI, and Tiger provides the knowhow in terms of how to really take that into action, solving a business problem. And specific markets and industry solutions that they have built also on top of our technology, which is great. So, that provides additional value for the customers.

Rebecca Knight

>> Can you share a specific example of how this partnership has helped solve a problem for a customer?

Rajeev Nayar

>> We had a joint press release about this. Trying to create an e-commerce platform where they were rethinking their digital search capability, and it's a unique sort of problem because they're in so many different markets, and there are so many languages and regions and all these considerations. And so, Google and Tiger partnered to first envision this solution and we started building out these solutions using Google Cloud capabilities and Vertex AI to basically solve the search problem. And the first market that they're going into is Thailand, but the intention is to go into multiple such markets. We actually helped to create an agentic platform for them where businesses could come in and define their own agents. So, we used ADK. And the interesting thing about this is that Google had announced ADK and we actually started implementation of ADK a week after it was announced.

Iliana Quinonez

>> You were one of the first few partners and customers of ours on that side too.

Rajeev Nayar

>> And that required us to work very closely together because anything new, there are obviously going to be challenges. And we work together. In fact, some of the things that we found is now making it into the product roadmap for Google.

Rebecca Knight

>> And so, what business value did that drive, solving the search problem? What was the result there?

Rajeev Nayar

>> So, the business problem we solved was for people in these markets to be able to get to the products that they wanted to buy.

Rebecca Knight

>> Kind of critical for business to get done.

Rajeev Nayar

>> And their ability to search for them in their native languages and be able to get to those products easily, that is the primary thing. It's directly related to the uplift of their business in these markets.

Rebecca Knight

>> Exactly. And helping customers find them and discover them and buy from them. What about some engagements with Vertex AI?

Rajeev Nayar

>> If you look at, we talked about creating value from data. So, Vertex AI has been an integral part of building these AI solutions. There's another customer, a very large fast-food chain, where we used Vertex AI and ADK to actually build their agent frameworks to deliver customer care agents. And there was another one about the restaurant management agents. You were asking about the business value. See, the customer care agent was about solving problems very quickly for the customers and creating an uplift in their business restaurant. They needed to manage their drive-through capabilities. We have all gone to these restaurants. And be able to address the queue length, the ability to service people faster and provide that uplift to business. That was the primary thing. And then, it's expanding now to where we are trying to work with them to develop a marketing-related agent to actually get an uplift in the return on investment on the marketing that they do. So, there are a number of such examples that we've been involved in and most of them result in these business outcomes, uplift of the business, reduction in the cost of service, for example, for an appliance manufacturer. We are in the process of reducing the cost for defective appliances from about $160 million to $40 million. So, these is tangible business outcomes that we're creating.

Rebecca Knight

>> Right. And we are all getting our milkshakes a little bit faster, which is critical too.

Rajeev Nayar

>> Especially in the drive-through.

Rebecca Knight

>> Iliana, what are you hearing from customers in terms of the feedback about this partnership?

Iliana Quinonez

>> Yeah, so I think a couple of things that come to mind. So, one is the fact that because Tiger has a strong partnership with us, they get access also to some of our new technologies a little bit earlier. They have the chance to actually prove them, try them, and then provide feedback to us. So, in that sense, well, we are the beneficiaries of getting the feedback from them using it themselves internally in the house. And then, when they go to customers. What that does is improve our roadmap. So, for our technology roadmap, super important to get that feedback very early on and often. And I think the other thing is that we are a technology company with a partner that brings value in terms of the consultancy and the advisory and the experience they have in building solutions on top of our technology. Rajeev was talking about Vertex AI, for instance. So, it's a vertical stack, fully integrated for AI applications, agentic framework, you can use all our tooling. But then, on top of that, Rajeev's company, Tiger, has this expertise of building their own tooling on top of that to complement what we are doing, and that gives them the edge in the solutions and the specific industries that we go together on, like retail and CPG for instance.

Rebecca Knight

>> And as you said, they're using it first to give you feedback on how to fine tune and make it better. Rajeev, Agentspace has been getting a lot of attention lately. Can you share some concrete examples about how it's being used?

Rajeev Nayar

>> Yeah. So, the appliance manufacturer that I was talking about, we actually worked together with Google in their process of adopting Agentspace. They didn't start with Agentspace. They wanted to actually move towards an agentic model for their business. And we bought in this idea of Agentspace and how that can be leveraged to do that. We are working with them to create about 30 to 60 agents. Many of them are being created by the customer themselves. There are about six or eight of them that are business critical that Tiger is owning up to build. But the idea over here is the adoption of Agentspace, while we adopt agents... What happens is when you start with actually building out these agents, you then find other problems in terms of your data and other things. And then, you help them to solve those problems, so that the business value can be delivered. And that's where the whole reduction in this defective appliances is coming in, where we are trying to reduce it from $160 million to $40 million.

Rebecca Knight

>> It helps them fix their data, but also understand how their workflows are and what the processes are, and how you can turn that into an agentic workflow.

Rajeev Nayar

>> Yeah, rethinking the processes. This is another thing because when you think about agentic solutions, it's not about automation only and you start rethinking your business processes and thinking about them differently and more efficiently-

Iliana Quinonez

>> Absolutely....

Rajeev Nayar

>> to create business value.

Iliana Quinonez

>> Yeah. And I think augmenting some of those workflows, sometimes, Rebecca, could actually also be in the picture. Sometimes it's automating, refining, augmenting, but in making a decision about which way to go, that's where the expertise from partners like Tiger comes in. Because the customer will be very new to the technology, also to the frameworks. And then, they need some handholding to go through that too.

Rebecca Knight

>> So, one thing about AI is that it's moving so fast. And the AI we're using today is going to be outdated and obsolete in six months. So, how do you see, Iliana, advances in AI and secure data, the joint roadmap between Tiger Analytics and Google Cloud?

Iliana Quinonez

>> Yeah, that's an excellent question, Rebecca. And it's like crystal balling, like what's going to happen next? But I think there's no question that we're seeing specific things that going, for instance, into next year are going to happen, that we're going to be working together very closely on. One is a whole data component of it. Obviously, that's one of the secret sources of Tiger in terms of how to leverage that story with data in terms of securing, bringing it in-house, leveraging, building upon it and building your business, your competitive advantage and differentiation from that. The second thing I would say is the agentic framework. So, agentic component, agentic applications are going to be there. Right now, we're just seeing the beginning of that. I think going into next year it's going to be full-fledged for companies out there. And the third thing I would say, Rajeev mentioned something very important, so the use of Agentspace. So, that is going to be the foundation for a lot of the agentic development in companies in the enterprise, and it's going to really solve a couple of problems. One is don't start from scratch. You already have a platform from which you can start building on. And then, on top of that, you have the expertise of Tiger to help you address very specific situations or issues that have to do with maybe marketing analytics or savings that you're trying to address. So, that combination is going to be very powerful. So, I would say agentic framework, the data story will continue and the security part of it too, because data is great, but you have to also secure it and you have to make sure that you know how to best reliably take advantage of it.

Rebecca Knight

>> You want to add to that?

Rajeev Nayar

>> Yes. So, there's actually a theme that Google had defined and we've sort of adopted that, which is win the data, live the data and secure the data. So, in many senses, we are actually coming up with services complementing what we are doing with Google. For win the data, we have something called migrate to modernize, where we are helping people move from where they are to this new platform. Lift the data is more about being able to use this data to create use cases and solutions that add value. And secure the data is about governing and managing the data, so that it's sustainable. So, we are in a lockstep in many cases with what Google is doing. Another important aspect over here, and again re-emphasize the rethinking part of it because at the end of it, it's about the delivery of business value. Where interestingly, what you're finding is as people get mature or start to get mature with their AI implementation, a lot of these AI capabilities, not the technical capabilities, but what is a requested of AI is driven by business. So, in many senses, technology takes a supporting role to what business wants and focusing on... One of the gaps that we fill with the partnership like Google is we try to understand the customer and map what they need to do to what Google brings to the table.

Iliana Quinonez

>> Yeah. And in a way to think about it's like bringing all that AI hype to AI reality, with how the technology has been evolving. So, getting our models, our foundational capabilities, the infrastructure and then with experience in the specific industries and that's really what's going to make a customer be more successful in their adoption of these new technologies, whichever those are when they come up again.

Rebecca Knight

>> Rajeev, what is next for Tiger Analytics in terms of what you're working on this year and how you are getting started with new customers, and then also expanding with customers who are already on their journey with you?

Rajeev Nayar

>> Actually, the expanding part is very interesting. If you look at the pattern, all the customers that we talked about, even in this session, what's happening is we start with these solutions and then it expands to helping them rethink their platforms, the data platforms, and being able to scale their AI initiatives. So, in many senses, we start with taking new technologies and new ideas to the customer, whether it's solutions from a domain perspective, I was talking about this earlier. When we are focused on CPG, we are focused on financial services, insurance, healthcare. So, taking new solutions to the customer that can deliver business value. And from there, helping them realize the value of what partners like Google bring to the table and expanding to make them rethink, so that they can become more efficient in how they use the data and AI.

Rebecca Knight

>> Final question for both of you. If you were to leave our audience with one piece of advice on how to move as, Iliana, you said, move from AI hype to real returns, real impact, what would that be? I'll start with you, Rajeev.

Rajeev Nayar

>> Multiple, but I'll address it. So, focus on ROI, right? It's easier said than done because you had to actually think through what is needed to deliver the ROI. You will have to focus on your data foundation because that becomes the basis on which your trusted platform, on which you can actually leverage your insights and decision making.

Rebecca Knight

>> Okay, excellent. So, think about your data. Yeah, it starts with data. Go on, Iliana.

Iliana Quinonez

>> So, I'm going to double down on that. Think about your data and think about your data as a currency. That's your new currency in business. And the best you can do with your data is acquire your data, leverage and leave your data and secure it, and then put it to good use, right? So, it's the new currency and that's an area that's not going to change. There's only going to be more data, more things to build up from. And then, just work with your partners and we're here for you.

Rebecca Knight

>> I love it. Iliana and Rajeev, a pleasure having you on theCUBE. A really interesting conversation.

Rajeev Nayar

>> Thank you.

Iliana Quinonez

>> Thank you so much, Rebecca. Thank you, Rajeev.

Rebecca Knight

>> And thank you for tuning into this edition of the Google Cloud Partner AI series. We'll hope you'll stay tuned for more.